1.101 – Le produit intérieur brut et ses composantes à prix courants (En milliards d’euros) - t_1101
Données - INSEE
Last observation: 2020 (N = 20)
First observation: 1949 (N = 20)
Last data update: 02 août 2026, 11:05
Last compile: 03 sept. 2026, 00:02
Structure
2020
Désordonné
Code
t_1101 |>
left_join(gdp, by = "date") |>
filter(date == as.Date("2020-01-01")) |>
select(-date) %>%
mutate(`% du PIB` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
value = round(value) |> paste0(" Mds€")) |>
select(-gdp) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Ordre
Code
t_1101 |>
left_join(gdp, by = "date") |>
filter(date == as.Date("2020-01-01")) |>
select(-date) |>
arrange(-value) %>%
mutate(`% du PIB` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
value = round(value) |> paste0(" Mds€")) |>
select(-gdp) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}2019
Désordonné
Code
t_1101 |>
left_join(gdp, by = "date") |>
filter(date == as.Date("2019-01-01")) |>
select(-date) %>%
mutate(`% du PIB` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
value = round(value) |> paste0(" Mds€")) |>
select(-gdp) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Ordre
Code
t_1101 |>
left_join(gdp, by = "date") |>
filter(date == as.Date("2019-01-01")) |>
select(-date) |>
arrange(-value) %>%
mutate(`% du PIB` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
value = round(value) |> paste0(" Mds€")) |>
select(-gdp) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Administration publique: Dépenses collective et individuelle
Code
t_1101 |>
filter(line %in% c(8, 10, 9)) |>
left_join(gdp, by = "date") |>
ggplot() + theme_minimal() + ylab("% du PIB") + xlab("") +
geom_line(aes(x = date, y = value/gdp, color = Line, linetype = Line)) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.85)) +
scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_y_log10(breaks = 0.01*seq(0, 100, 1),
labels = scales::percent_format(accuracy = 1))
GDP Components
Code
t_1101 |>
filter(line %in% c(8, 12, 9)) |>
left_join(gdp, by = "date") |>
ggplot() + theme_minimal() + ylab("% du PIB") + xlab("") +
geom_line(aes(x = date, y = value/gdp, color = Line, linetype = Line)) +
theme(legend.title = element_blank(),
legend.position = c(0.7, 0.15)) +
scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_y_log10(breaks = 0.01*seq(0, 100, 1),
labels = scales::percent_format(accuracy = 1))
Investissement et taux de marge
Code
t_1101 |>
filter(line %in% c(12)) |>
left_join(gdp, by = "date") |>
mutate(value = value/gdp) |>
select(Variable = Line, date, value) |>
mutate(Variable = "Investissement (% du PIB)") |>
bind_rows(t_txmargesnf_val |>
filter(variable == "taux_marge") |>
mutate(Variable = "Taux de marge") |>
mutate(value = value/100)) |>
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = value, color = Variable)) +
theme(legend.title = element_blank(),
legend.position = c(0.3, 0.9)) +
scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(3)[1:2]) +
scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
labels = scales::percent_format(accuracy = 1))